Evaluation of NASA POWER and ERA5-Land for estimating tropical precipitation and temperature extremes

Journal of Hydrology, Год журнала: 2023, Номер 624, С. 129940 - 129940

Опубликована: Июль 20, 2023

Язык: Английский

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Assessment of climatic influences on net primary productivity along elevation gradients in temperate ecoregions

Trees Forests and People, Год журнала: 2024, Номер 18, С. 100657 - 100657

Опубликована: Авг. 20, 2024

Язык: Английский

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Machine Learning and Spatio Temporal Analysis for Assessing Ecological Impacts of the Billion Tree Afforestation Project

Ecology and Evolution, Год журнала: 2025, Номер 15(2)

Опубликована: Фев. 1, 2025

ABSTRACT This study evaluates the Billion Tree Afforestation Project (BTAP) in Pakistan's Khyber Pakhtunkhwa (KPK) province using remote sensing and machine learning. Applying Random Forest (RF) classification to Sentinel‐2 imagery, we observed an increase tree cover from 25.02% 2015 29.99% 2023 a decrease barren land 20.64% 16.81%, with accuracy above 85%. Hotspot spatial clustering analyses revealed significant vegetation recovery, high‐confidence hotspots rising 36.76% 42.56%. A predictive model for Normalized Difference Vegetation Index (NDVI), supported by SHAP analysis, identified soil moisture precipitation as primary drivers of growth, ANN achieving R 2 0.8556 RMSE 0.0607 on testing dataset. These results demonstrate effectiveness integrating learning framework support data‐driven afforestation efforts inform sustainable environmental management practices.

Язык: Английский

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Large-sample hydrology – a few camels or a whole caravan?

Hydrology and earth system sciences, Год журнала: 2024, Номер 28(17), С. 4219 - 4237

Опубликована: Сен. 12, 2024

Abstract. Large-sample datasets containing hydrometeorological time series and catchment attributes for hundreds of catchments in a country, many them known as “CAMELS” (Catchment Attributes MEteorology Studies), have revolutionized hydrological modelling enabled comparative analyses. The Caravan dataset is compilation several (CAMELS other) large-sample with uniform attribute names data structures. This simplifies hydrology across regions, continents, or the globe. However, use instead original CAMELS other may affect model results conclusions derived thereof. For dataset, meteorological forcing are based on ERA5-Land reanalysis data. Here, we describe differences between precipitation, temperature, potential evapotranspiration (Epot) 1252 CAMELS-US, CAMELS-BR, CAMELS-GB these dataset. Epot unrealistically high catchments, but there are, unsurprisingly, also considerable precipitation We show that from impairs calibration vast majority catchments; i.e. drop performance when using compared to datasets. mainly due Therefore, suggest extending included wherever possible so users can choose which they want at least indicating clearly come quality loss recommended. Moreover, not (and attributes, such aridity index) recommend should be replaced (or on) alternative estimates.

Язык: Английский

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Obtaining refined Euro-Mediterranean rainfall projections through regional assessment of CMIP6 General Circulation Models

Global and Planetary Change, Год журнала: 2025, Номер unknown, С. 104725 - 104725

Опубликована: Янв. 1, 2025

Язык: Английский

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Benefits and pitfalls of irrigation timing and water amounts derived from satellite soil moisture

Agricultural Water Management, Год журнала: 2024, Номер 295, С. 108773 - 108773

Опубликована: Март 13, 2024

Despite the key role of irrigation in Earth system, we lack fundamental information regarding distribution irrigated fields, timing and amount water utilized. In past years, SM_Delta SM_Inversion approaches have been independently developed to provide estimates amounts based on satellite soil moisture data. The approach retrieves from variations between an individual pixel surrounding rainfed area, while total entering soil, then is derived by subtracting precipitation. this study, perform a comprehensive assessment algorithms Sentinel-1 surface retrievals at 1 km resolution. Our analysis focuses Ebro basin, region Spain covering 83000 km2, during period 2017–2019. We assess ability two methods discriminate pixels, quantify agreement volumes with reference An inter-comparison carried out considering both temporal spatial features, i.e., monthly peaks patterns. Finally, explore potential applications satellite-derived estimates: attributing specific systems crops. observe that erroneously retrieve over are therefore not suitable map fields. However, when auxiliary fields available, find satisfactory district-scale data satellite-retrieved irrigation, using (Pearson R equal 0.67 0.71, bias −4.99 −4.75 mm/15 days, respectively). When aggregated space or time, exhibit coherent dynamics For instance, capture delayed occurred 2018 due wetter than usual conditions spring. pixel-scale, limited consistency exists different assumptions parameterizations, e.g., use constant vs pixel-specific capacity (in SM_Inversion, Overall, study demonstrates reliability approaches, especially shifting small short scales (pixel level, sub-weekly) larger longer (district seasonal). Hence, satellite-based could inform resources managers basin authorities, as well serve modelling community providing reliable employed level.

Язык: Английский

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Assessing Changes in Exceptional Rainfall in Portugal Using ERA5-Land Reanalysis Data (1981/1982–2022/2023)

Water, Год журнала: 2024, Номер 16(5), С. 628 - 628

Опубликована: Фев. 20, 2024

This research examines the intricate changes in number of occurrences and cumulative rainfall exceptional events Portugal spanning 42 hydrological years (from 1981/1982 to 2022/2023). The study has two primary objectives: assessing spatial dynamics a region susceptible climate-induced variations evaluating proficiency ERA5-Land reanalysis dataset capturing rainfall. Confronting methodological data-related challenges (e.g., incomplete record series), investigation uses continuous daily series. Validation against Sistema Nacional de Informação Recursos Hídricos (SNIRH) Portuguese Institute for Sea Atmosphere (IPMA) ensures reliability data. Empirical non-exceedance probability curves reveal broad consensus between data observational records, establishing dataset’s suitability subsequent analysis. Spatial representations occurrences, rainfall, intensity above thresholds throughout overall 42-year period subperiods (late: 1981/1982–2001/2002; recent: 2002/2003–2022/2023) are presented, illustrating temporal variations. A noteworthy shift distribution intense from south north is observed, emphasising dynamism such processes. introduces novel dimension with severity heat map, combining some key findings through subperiods. significantly contributes understanding Portugal, providing valuable insights risk management development sustainable strategies tailored evolving patterns

Язык: Английский

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Exploring Recent (1991–2020) Trends of Essential Climate Variables in Greece

Atmosphere, Год журнала: 2024, Номер 15(9), С. 1104 - 1104

Опубликована: Сен. 11, 2024

Europe and the Mediterranean are considered climate change hot spots. This is reason why this paper focuses on analysis of trends essential variables in a country, Greece. The analyzed period 1991–2020, dataset used ERA5-Land (produced by European Center for Medium-Range Weather Forecasts), which has global coverage an improved resolution ~9 × 9 km compared to other datasets. Significant climatic changes across Greece have been put evidence during period. More specifically, country averaged 30-year trend temperature +1.5 °C, locally exceeding +2 increasing positively correlated with distance areas from coasts. Accordingly, number frost days decreased throughout country. In terms rainfall, major part experienced annual rainfall amounts, while 86% Greek area positive heavy (>20 mm). Finally, multiple signal consecutive dry was found (statistically non-significant Greece).

Язык: Английский

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Using ERA-5 LAND reanalysis rainfall data to better evaluate the performance of the regional shallow landslide early warning system of Piemonte (north-western Italy) in the context of climate change

Frontiers in Earth Science, Год журнала: 2025, Номер 12

Опубликована: Янв. 8, 2025

To correctly understand how and whether climate change has influenced the behavior of shallow landslide events over last century, it is essential to carefully identify historical series phenomena their respective triggering causes, as well accurately select most appropriate analytical tools minimize degree uncertainty in statistical correlation causes effects. Shallow occurring from 1960 2023 Piemonte (NW Italy) are considered here, for which primary cause represented by rainfall events, with a negligible contribution antecedent precipitations. This paper an update previous study, adding analysis recent widespread covering wider time range new precipitation data (additional 4 years). The difference lies use different method analyze responsible occurrence landslides. In particular, results obtained 24 48 h durations, when compared thresholds R-SLEWS (previously employed Optimal Interpolation Method), verified using more flexible reconstructing based on ERA5-Land hourly data. approach moderately improves identification actual but less performant comes identifying landslides h. Where no significant improvements detection rainfall-inducing obtained, can still be effectively used areas sparser rain gauge network, rely observed

Язык: Английский

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Empirical methods to determine surface air temperature from satellite-retrieved data

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2025, Номер 136, С. 104380 - 104380

Опубликована: Янв. 23, 2025

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